bayesreg: Bayesian Regression Models with Global-Local Shrinkage Priors

Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arXiv:1611.06649>.

Package details

AuthorDaniel F. Schmidt [aut, cph, cre] (<>), Enes Makalic [aut, cph] (<>)
MaintainerDaniel F. Schmidt <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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bayesreg documentation built on March 29, 2021, 9:11 a.m.